Localisation, or positioning, is the estimation of the location of one or more mobile targets, either in absolute terms or relative to a fixed position. Wireless positioning systems in which the target is equipped with a wireless transmitter and/or receiver are widely used in location based services such as surveillance and monitoring, person and asset tracking, public safety, and emergency rescue. Known techniques for wireless positioning include those based on time-of-arrival (ToA) measurements and/or direction-of-arrival (DoA) measurements. ToA-based wireless positioning systems normally require the setting up of multiple fixed anchor or referencing nodes. The range from a target to each anchor/referencing node can be estimated from the ToA measurement. With the knowledge of the spatial location of the fixed anchor/referencing nodes, multilateration may be performed to estimate the location of the target. DoA-based systems also require multiple fixed anchor/referencing nodes. However, instead of measuring the range from the target, each anchor/referencing node estimates the incident angle of a signal transmitted from the target, for example using an antenna array. The location of the target can be estimated using the measured DoAs, using triangulation from the known locations of the anchor/referencing nodes. The DoA is usually determined using the phase of the signal from a plurality of elements in an antenna array. However, the spacing between the array elements is limited by the need to avoid phase ambiguity, which results in multiple solutions for the DoA of the received signal. This puts either an upper limit on the aperture width of the array, and hence the resolution of the DoA estimate, or a lower limit on the number of elements, which increases the computational complexity.
For many applications, it is desirable to have a positioning system in which a single nomadic “master node” can communicate with all the targets so the locations of the latter can be estimated by the former. In one example scenario, a large number of workers, each equipped with a radio frequency “tag”, are scattered around a worksite. For safety reasons, a manager at the master node, which is also mobile, needs to know the location of each worker at all times. Conventional triangulation-based positioning systems using ToA or DoA alone cannot be used because there is only a single anchor node, namely the master node. Joint ToA/DoA-based positioning, involving both ToA and DoA measurements, may be used to estimate the tag locations. However, joint ToA/DoA location estimation is typically a computationally intensive problem. The optimal maximum-likelihood (ML) estimation involves a two-dimensional (2D) search over the range and bearing to maximize the probability density function of the received signals at all antenna elements at the master node, conditioned on the signal ToAs and DoAs.
To reduce the complexity, several efficient algorithms based on the ML principle have been developed, such as the expectation maximization (EM) and the space-alternating generalized expectation maximization (SAGE). Another category of joint ToA/DoA estimation algorithms is based on the subspace principle. These algorithms include the joint angle and delay estimation (JADE), and the multi-dimensional estimation of signal parameters via rotational invariance technique (MD-ESPRIT). However, such techniques are still too computationally intensive to be implemented in a practical wireless positioning system for the above-mentioned scenario.